Package: dnr 0.3.5

dnr: Simulate Dynamic Networks using Exponential Random Graph Models (ERGM) Family

Functions are provided to fit temporal lag models to dynamic networks. The models are build on top of exponential random graph models (ERGM) framework. There are functions for simulating or forecasting networks for future time points. Abhirup Mallik & Zack W. Almquist (2019) Stable Multiple Time Step Simulation/Prediction From Lagged Dynamic Network Regression Models, Journal of Computational and Graphical Statistics, 28:4, 967-979, <doi:10.1080/10618600.2019.1594834>.

Authors:Abhirup Mallik [aut, cre], Zack Almquist [aut]

dnr_0.3.5.tar.gz
dnr_0.3.5.zip(r-4.5)dnr_0.3.5.zip(r-4.4)dnr_0.3.5.zip(r-4.3)
dnr_0.3.5.tgz(r-4.5-any)dnr_0.3.5.tgz(r-4.4-any)dnr_0.3.5.tgz(r-4.3-any)
dnr_0.3.5.tar.gz(r-4.5-noble)dnr_0.3.5.tar.gz(r-4.4-noble)
dnr_0.3.5.tgz(r-4.4-emscripten)dnr_0.3.5.tgz(r-4.3-emscripten)
dnr.pdf |dnr.html
dnr/json (API)

# Install 'dnr' in R:
install.packages('dnr', repos = c('https://abhirupkgp.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • beach - Dynamically changing network of inter personal communication among the visitors of a beach in southern California.
  • rdNets - Blog citation network

On CRAN:

Conda-Forge:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.95 score 18 scripts 194 downloads 13 exports 55 dependencies

Last updated 4 years agofrom:91fcd30f8c. Checks:1 OK, 7 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 21 2025
R-4.5-winNOTEFeb 21 2025
R-4.5-macNOTEFeb 21 2025
R-4.5-linuxNOTEFeb 21 2025
R-4.4-winNOTEFeb 21 2025
R-4.4-macNOTEFeb 21 2025
R-4.3-winNOTEFeb 21 2025
R-4.3-macNOTEFeb 21 2025

Exports:binaryPlotclustCoefengineEdgeengineEdgeNSengineVertexengineVertexNSexpdegntrianglesparamEdgeparamVertexparamVertexOnlyparamVertexOnlyGroupvdegree

Dependencies:abindarmbootcachemclicodacodetoolscpp11DEoptimRergmevaluatefansifastmapforeachglmnetgluehighrigraphiteratorsknitrlatticelifecyclelme4lpSolveAPImagrittrMASSMatrixmemoiseminqanetworknlmenloptrpillarpkgconfigpurrrrbibutilsRcppRcppEigenRdpackreformulasrlangrlerobustbaseshapesnastatnet.commonstringistringrsurvivaltibbletrustutf8vctrsxfunyaml

Dynamic Network Regression Using dnr

Rendered fromdnr_vignette.Rnwusingknitr::knitron Feb 21 2025.

Last update: 2020-11-30
Started: 2018-02-23